We posited that the analysis of funded grants will elucidate the national-global interplay to achieve health MDGs, especially the short- and medium-term action proposals and budget allocations for research-related activities.
These analyses provide an important global summary of interplay between pathways, and they identify processes, process associations and dataset similarities likely to benefit from experimental investigation.
Understanding the molecular pathogenesis and underlying biology in ovarian cancer through the global view on interplays between different levels of genomic data is expected to provide guidance for improved prognostic indicators and effective therapies.
Taken together these results suggest that meta-dimensional model will lead us to an enhanced global view on interplays since different levels of genomic data might affect the cancer phenotype through either partly independent or partly complementary fashion.
Understanding the molecular pathogenesis and underlying complex mechanisms in ovarian cancer through the global view on interplays between them is expected to provide guidance for improved prognostic indicators and effective therapies [ 33].
As different levels of genomic data such as copy number, SNP, methylation, or miRNA, might affect gene regulation through either specific or synergistic fashion, an integrative framework that incorporates all these different genomic features as potential regulators of gene expression will lead us to an enhanced global view on interplays between them.
Since different levels of genomic data might affect gene regulation through either partly independent or partly complementary fashion, proposed framework that incorporates all these different genomic features as potential regulators of gene expression will lead us to an enhanced global view on interplays between them.
While the TCGA and ICGC open many opportunities to deepen the knowledge of the molecular basis of cancer [ 16- 19], it is particularly important to integrate different levels of genomic data at hand for providing an enhanced global view on interplays between them.
While the TCGA and ICGC open many opportunities to deepen the knowledge of the molecular basis of cancer [ 27- 29], it is particularly important to access different levels of genomic data at hand for providing an enhanced global view on interplays between them.
We assume that accuracy of prediction model increase when considering of inter-relationship between different levels of genomic data because of incorporation of information fused over genomic dataset and genomic knowledge, providing an enhanced global view on interplays in cancer mechanisms [ 12, 18].
